A Comparison of Discrete and Continuous Metrics for Measuring Landscape Changes

Quantification of landscape patterns in a correct way is an important issue in landscape ecology, which has recently attracted much attention from landscape ecologists. It is believed that Patch-Corridor-Matrix or discrete model does not take into account the continuous heterogeneity and has limitations and problems that undermine the validity of the results. Various continuous methods have been developed to overcome the problems associated with the discrete approach for measuring landscape fragmentation. Continuous methods use remotely sensed data directly for quantifying landscape pattern changes. In this regard, the purpose of this study is to compare landscape metrics obtained from the discrete model and alternative continuous metrics, including spatial autocorrelation indices, Fourier transforms, and surface metrics. To achieve this goal, we used two subsets that were different in terms of urban and agricultural changes. We measured temporal changes of three subsets between the years 2013 and 2020. Results showed that percentage of landscape (PLAND) as a landscape metric had a good statistical relationship with Getis of the normalized difference vegetation index (NDVI) (R 2 = 95.9%) and a moderate relationship with Getis of the built-up index (PNBI) (R 2 = 43.7%) as alternative metrics. The results of discrete metrics showed that in 2013, the spatial patterns of urban and cultivated farms patches were more fragmented than in 2020. Also, the area of cultivated farms increased by 3 to 6 percent and urban areas between 1 and 8 percent in 2020. All continuous metrics showed that the subsets in the study changed in 2020. However, Fourier transforms could not determine the magnitude of these changes. Our results also showed that landscape metrics have some drawbacks for measuring landscape patterns that some of them can be resolved by continuous metrics. Generally, the use of discrete and continuous metrics depends on factors like the scale of the study, time and budget available, desired ecological processes, and the degree of heterogeneity of the landscape of interest.